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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗
NASA NTRS1987

Analysis of adaptive identifiers in the presence of unmodelled dynamics: Averaging and tuned parameters

The behavior of a standard identifier is analyzed for the case in which the plant contains additional dynamics, called unmodeled dynamics, which invalidate the known order assumption. An input richness condition is obtained that does not depend on the order of the unmmodeled dynamics to guarantee persistency of excitation (PE) of the regressor. It is shown that the PE condition leads to a BIBO stability property for the identifier. The method of averaging is used to define formally the notion of tuned parameters as the equilibrium of the identifier-averaged system. It is shown that the tuned parameters always exist and that the actual parameters converge to some neighborhood of the tuned parameters. An explicit expression is derived to calculate and interpret them as the fixed parameter values that minimize the mean-squared output error.

Mason, J. E.↗
DOE OSTI2022

East Asian Rainbands and Associated Circulation over the Tibetan Plateau Region

Abstract Rainbands that migrate northward from spring to summer are persistent features of the East Asian summer monsoon. This study employs a machine learning algorithm to identify individual East Asian rainbands from May to August in the 6-hourly ERA-Interim reanalysis product and captures rainband events during these months for the period 1979–2018. The median duration of rainband events at any location in East Asia is 12 h, and the centroids of these rainbands move northward continuously from approximately 28°N in late May to approximately 33°N in July, instead of making jumps between quasi-stationary periods. Whereas the length and overall area of the rainbands grow monotonically from May to June, the intensity of the rainfall within the rainband dips slightly in early June before it peaks in late June. We find that extratropical northerly winds on all pressure levels over East China are the most important anomalous flow accompanying the rainband events. The anomalous northerlies augment climatological background northerlies in bringing low moist static energy air and thus generate the front associated with the rainband. Persistent lower-tropospheric southerly winds bring in moisture that feeds the rainband and are enhanced a few days prior to rainband events, but they are not directly tied to the actual rainband formation. The background northerlies could originate as part of the Rossby waves resulting from the jet stream interaction with the Tibetan Plateau. The ageostrophic circulation in the jet entrance region peaks in May and weakens in June and July and does not prove to be critical to the formation of the rainbands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A comparative investigation of the effect of gas type on foam strength and flow behavior in tight carbonates

Foam generation technique has been practically applied to overcome gas mobility issue during enhanced oil recovery (EOR) processes. Incorporated with the utilized gas, the capability of foaming agent to generate persistent foam determines the flow performance under reservoir conditions. Here, in this study, we first identified the surfactants with excellent phase behavior and foaming properties and, second, evaluated their bulk foam performance with different gases, including N 2 , CO 2 , and hydrocarbon gas (CH 4 ) under high-pressure and high-temperature conditions. In bulk, the foam generated with the high-density gas, i.e., CO 2 , exhibited the greatest foamability but the lowest foam stability. With amidoamine oxide-based surfactant, CH 4 -foam was found to be more stable than N 2 -foam, while the opposite was observed for sulfobetaine-based surfactant. The most effective surfactant was later used to perform flow experiments on two tight carbonate rocks, including Minnesota Norther Cream Buff and Edwards limestone, with permeabilities of ~0.8 and 16 mD, respectively. The core-flooding experiments showed that the optimum quality of CO 2 -foam was lower than that of N 2 - and CH 4 -foams. For a given flow rate and fixed foam quality, the steady-state strength followed the descending order of CH 4 -, N 2 -, and CO 2 -foam. However, in general, the difference in foam strength between N 2 - and CH 4 -foams was insignificant when the total flow rate was varied. We also found that the variation in rock permeability had a greater effect on the strength of the CO 2 -foam compared to those generated with N 2 and CH 4 . In the presence of oil, the shear-thinning behavior of all foams was found more prominent. The increase in oil saturation had a more adverse effect on the strength of N 2 - and CH 4 -foams, particularly in the higher permeability rock. The results indicated that the foam strength, which is key in the effectiveness of foam EOR applications, is greatly influenced by several factors such as gas density, gas solubility in water, the presence of oil, and rock permeability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Chemical trends of deep levels in van der Waals semiconductors

Abstract Properties of semiconductors are largely defined by crystal imperfections including native defects. Van der Waals (vdW) semiconductors, a newly emerged class of materials, are no exception: defects exist even in the purest materials and strongly affect their electrical, optical, magnetic, catalytic and sensing properties. However, unlike conventional semiconductors where energy levels of defects are well documented, they are experimentally unknown in even the best studied vdW semiconductors, impeding the understanding and utilization of these materials. Here, we directly evaluate deep levels and their chemical trends in the bandgap of MoS 2 , WS 2 and their alloys by transient spectroscopic study. One of the deep levels is found to follow the conduction band minimum of each host, attributed to the native sulfur vacancy. A switchable, DX center - like deep level has also been identified, whose energy lines up instead on a fixed level across different hosts, explaining a persistent photoconductivity above 400 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Nanoscale Conductivity Imaging of Correlated Electronic States in WSe 2 /WS 2 Moiré Superlattices

We report the nanoscale conductivity imaging of correlated electronic states in angle-aligned WSe 2 /WS 2 heterostructures using microwave impedance microscopy. Here, the noncontact microwave probe allows us to observe the Mott insulating state with one hole per moiré unit cell that persists for temperatures up to 150 K, consistent with other characterization techniques. In addition, we identify for the first time a Mott insulating state at one electron per moiré unit cell. Appreciable inhomogeneity of the correlated states is directly visualized in the hetero-bilayer region, indicative of local disorders in the moiré superlattice potential or electrostatic doping. Our work provides important insights on 2D moiré systems down to the microscopic level.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Hydrodynamics of higher-rank gauge theories

We extend recent work on hydrodynamics with global multipolar symmetries — known as “fracton hydrodynamics” — to systems in which the multipolar symmetries are gauged. We refer to the latter as “fracton magnetohydrodynamics”, in analogy to conventional magnetohydrodynamics (MHD), which governs systems with gauged charge conservation. We show that fracton MHD arises naturally from higher-rank Maxwell’s equations and in systems with one-form symmetries obeying certain constraints; while we focus on “minimal” higher-rank generalizations of MHD that realize diffusion, our methods may also be used to identify other, more exotic hydrodynamic theories (e.g., with magnetic subdiffusion). In contrast to semi-microscopic derivations of MHD, our approach elucidates the origin of the hydrodynamic modes by identifying the corresponding higher-form symmetries. Being rooted in symmetries, the hydrodynamic modes may persist even when the semi-microscopic equations no longer provide an accurate description of the system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1999

The Global Precipitation Patterns Associated with Short-Term Extratropical Climate Fluctuations

Two globally-complete, observation-only precipitation datasets have recently been developed for the Global Precipitation Climatology Project (GPCP). Both depend heavily on a variety of satellite input, as well as gauge data over land. The first, Version 2x79, provides monthly estimates on a 2.5 deg. x 2.5 deg. lat/long grid for the period 1979 through late 1999 (by the time of the conference). The second, the One-Degree Daily (1DD), provides daily estimates on a 1 deg. x l deg. grid for the period 1997 through late 1999 (by the time of the conference). Both are in beta test preparatory to release as official GPCP products. These datasets provide a unique perspective on the hydrological effects of the various atmospheric flow anomalies that have been identified by meteorologists. In this paper we discuss the regional precipitation effects that result from persistent extratropical flow anomalies. We will focus on the Pacific-North America (PNA) and North Atlantic Oscillation (NAO) patterns. Each characteristically becomes established on synoptic time scales, but then persists for periods that can exceed a month. The onset phase of each appears to have systematic mobile features, while the mature phase tend to be more stationary. Accordingly, composites of monthly data for outstanding positive and negative events (separately) contained in the 20-year record reveal the climatological structure of the precipitation during the mature phase. The climatological anomalies of the positive, negative, and (positive-negative) composites show the expected storm-track-related shifts in precipitation, and provide the advantage of putting the known precipitation effects over land in the context of the total pattern over land and ocean. As well, this global perspective points out some unexpected areas of correlation. Day-by-day composites of daily data anchored to the onset date demonstrate the systematic features during the onset. Although the 1DD has a fairly short record, some preliminary results are shown and compared to previous work with numerical weather prediction models.

Huffman, George J.↗
NASA NTRSDate not supplied

Seed surface sanitization and persistence of E.coli through different tissues of ‘Red Robin’ Tomato (Solanum lycopersicum cv. Red Robin)

Seed surface sanitization via chemical processes removes/reduces microbes from the external surfaces of the seed and thereby could have an impact on the plants’ health or productivity. To determine the impact of seed surface sanitization on the plants’ microbiome, sanitized and unsanitized seeds from ‘Red Robin’ Tomato (Solanumlycopersicum cv. Red Robin) were exposed to Escherichia coli (E. coli) and grown in a controlled environment growth chamber simulating environmental conditions aboard the International Space Station (ISS). Plants were harvested at four intervals, days 11, 33,42 and 76 post-germination. Changes in the microbial communities of leaf, stem, root, and fruit because of E. coli exposure and the persistence of E. coli itself were investigated using aerobic plate count (APC), qPCR and 16S rRNA sequencing. It was determined that E. coli persisted for longer periods of time in plants from sanitized versus unsanitized seeds and was identified in root tissue more frequently than in leaf or stem tissue. E. coli was not detected in fruits raised from either sanitized or unsanitized seeds. The 16S rRNA sequencing showed dynamic changes in the abundance of members of the phylum Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes in all tissue types studied. We observed minimal or no changes in the alpha diversity of leaf stem and fruit tissue with time, or between sanitized and unsanitized seeds. Roots showed significant differences in alpha diversity with time and seed sanitization status. Beta-diversity showed that time had more of an influence on all samples versus the E. coli treatment. Members of phyla Proteobacteria and Bacteroidetes were found to be differentially abundant across leaf, stem and root tissue. Our results indicated that the seed surface sanitization, although a requirement for sending seeds to space, might influence the developing microbiome. This research was funded by NASA’s Space Life and Physical Sciences Research and Applications.

Anirudha R Dixit↗
NASA NTRSDate not supplied

Enterococci in Space: Adaptation, Antibiotic Resistance, and Clinical Implications

Enterococci are gram-positive bacteria that originated when our ancient animal ancestors emerged from the oceans to live on land, and brought their gut flora with them. Enterococcus faecalis (EF) and Enterococcus faecium, are common human commensals and can harbor multidrug resistance. Both have been previously isolated from the International Space Station (ISS). Likely as a consequence of their evolutionary origins, enterococci show remarkable stress resistance within, but also outside, their human hosts. Their antibiotic resistance, coupled with tolerance to desiccation, starvation, and disinfection, make some EF strains potent pathogens in the built environment (e.g., hospitals), and a potential risk to crew health during space missions. Here we describe our planned flight studies, currently in development. Genomic Enumeration of Antibiotic Resistance in Space (GEARS) will characterize the frequency and genomic identity of antibiotic resistant organisms, including enterococci, on the ISS, and expand our future in-space sequencing-based diagnostic capabilities. Enterococcus Growth Advantage on ISS via Tn-seq (EnteroGAIT) will assess the evolutionary selective pressure of the space environment (microgravity, space radiation) using EF as a model system during a long-duration culture and persistence experiment. Adaptation & Evolution of Resilient Enterococcus in Space (AERES) will study existing and newly identified isolates to characterize the “natural” evolutionary history of EF on Earth and in space to reveal mechanisms of microbial adaption including, possibly, natural selection. Our work to date has identified that EF ISS isolates share virulence factors found in clinical strains and commensals, and revealed limitations of current pathogenicity assessment tools. While ISS isolates were, in some cases, multi-drug resistant, current data suggests these are largely commensal strains. Our work will further refine potential crew health risks and improve understanding of EF adaptation to the built environment, of great relevance on Earth where EF is the second leading cause of hospital acquired infection.

Jordan McKaig↗
DOE OSTI2021

Persistent arsenate–iron( iii ) oxyhydroxide–organic matter nanoaggregates observed in coal

Understanding how natural nanoaggregates of iron (Fe) and organic matter (OM), currently identified in organic rich soil or peat, interact with metals and metalloids is environmentally significant. Here, coal is also organic-rich and exemplifies anoxic sedimentary environments with Fe usually as pyrite and not oxides. Here, we analyze the local structure of Fe (6880–21 700 mg kg –1 ) and As (45–5680 mg kg –1 ) in representative Guizhou coal samples using X-ray absorption near-edge structure and extended X-ray absorption fine structure (XANES and EXAFS) to illustrate how Fe(III) and As(V) are preserved in coal formed from reduced, organic-rich precursors. Arsenic XANES indicates that >80% of As exists as As(V) with <14% of As associated with sulfides in 5 Guizhou coal samples, confirming published but unexplained results. An As–Fe shell at 3.25–3.29 Å in the As EXAFS suggests that this As(V) is adsorbed on Fe(III) oxyhydroxides as evidenced by Fe EXAFS in these coal samples. Significantly, lower Fe–Fe coordination numbers (CN) of 0.6–1.1 relative to those in 2-line ferrihydrite (CN = 1.6) and goethite (CN = 2.1) suggest that these Fe(III) oxyhydroxides are likely Fe–OM nanoaggregates protected by OM encapsulation and adsorption of arsenate. Such structurally stabilized composites of As(V)–Fe(III)–OM may be more widely distributed and allow oxidized As and Fe to persist in other organic-rich, reducing environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Application of advanced causal analyses to identify processes governing secondary organic aerosols

Abstract Understanding how different physical and chemical atmospheric processes affect the formation of fine particles has been a persistent challenge. Inferring causal relations between the various measured features affecting the formation of secondary organic aerosol (SOA) particles is complicated since correlations between variables do not necessarily imply causality. Here, we apply a state-of-the-art information transfer measure coupled with the Koopman operator framework to infer causal relations between isoprene epoxydiol SOA (IEPOX-SOA) and different chemistry and meteorological variables derived from detailed regional model predictions over the Amazon rainforest. IEPOX-SOA represents one of the most complex SOA formation pathways and is formed by the interactions between natural biogenic isoprene emissions and anthropogenic emissions affecting sulfate, acidity and particle water. Since the regional model captures the known relations of IEPOX-SOA with different chemistry and meteorological features, their simulated time series implicitly include their causal relations. We show that our causal model successfully infers the known major causal relations between total particle phase 2-methyl tetrols (the dominant component of IEPOX-SOA over the Amazon) and input features. We provide the first proof of concept that the application of our causal model better identifies causal relations compared to correlation and random forest analyses performed over the same dataset. Our work has tremendous implications, as our methodology of causal discovery could be used to identify unknown processes and features affecting fine particles and atmospheric chemistry in the Earth’s atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Metaproteomics reveals insights into microbial structure, interactions, and dynamic regulation in defined communities as they respond to environmental disturbance

Abstract Background Microbe-microbe interactions between members of the plant rhizosphere are important but remain poorly understood. A more comprehensive understanding of the molecular mechanisms used by microbes to cooperate, compete, and persist has been challenging because of the complexity of natural ecosystems and the limited control over environmental factors. One strategy to address this challenge relies on studying complexity in a progressive manner, by first building a detailed understanding of relatively simple subsets of the community and then achieving high predictive power through combining different building blocks (e.g., hosts, community members) for different environments. Herein, we coupled this reductionist approach with high-resolution mass spectrometry-based metaproteomics to study molecular mechanisms driving community assembly, adaptation, and functionality for a defined community of ten taxonomically diverse bacterial members of Populus deltoides rhizosphere co-cultured either in a complex or defined medium. Results Metaproteomics showed this defined community assembled into distinct microbiomes based on growth media that eventually exhibit composition and functional stability over time. The community grown in two different media showed variation in composition, yet both were dominated by only a few microbial strains. Proteome-wide interrogation provided detailed insights into the functional behavior of each dominant member as they adjust to changing community compositions and environments. The emergence and persistence of select microbes in these communities were driven by specialization in strategies including motility, antibiotic production, altered metabolism, and dormancy. Protein-level interrogation identified post-translational modifications that provided additional insights into regulatory mechanisms influencing microbial adaptation in the changing environments. Conclusions This study provides high-resolution proteome-level insights into our understanding of microbe-microbe interactions and highlights specialized biological processes carried out by specific members of assembled microbiomes to compete and persist in changing environmental conditions. Emergent properties observed in these lower complexity communities can then be re-evaluated as more complex systems are studied and, when a particular property becomes less relevant, higher-order interactions can be identified.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2013

Influence of Persistent Wind Scour on the Surface Mass Balance of Antarctica

Accurate quantification of surface snow accumulation over Antarctica is a key constraint for estimates of the Antarctic mass balance, as well as climatic interpretations of ice-core records. Over Antarctica, near-surface winds accelerate down relatively steep surface slopes, eroding and sublimating the snow. This wind scour results in numerous localized regions (< or = 200 sq km) with reduced surface accumulation. Estimates of Antarctic surface mass balance rely on sparse point measurements or coarse atmospheric models that do not capture these local processes, and overestimate the net mass input in wind-scour zones. Here we combine airborne radar observations of unconformable stratigraphic layers with lidar-derived surface roughness measurements to identify extensive wind-scour zones over Dome A, in the interior of East Antarctica. The scour zones are persistent because they are controlled by bedrock topography. On the basis of our Dome A observations, we develop an empirical model to predict wind-scour zones across the Antarctic continent and find that these zones are predominantly located in East Antarctica. We estimate that approx. 2.7-6.6% of the surface area of Antarctica has persistent negative net accumulation due to wind scour, which suggests that, across the continent, the snow mass input is overestimated by 11-36.5 Gt /yr in present surface-mass-balance calculations.

Antarctica↗
DOE OSTI2025

Short-range spin freezing in the double trillium lattice spin-liquid candidate KSrFe 2 ⁢(PO 4 ) 3 revealed via 31 P NMR

A comprehensive 31 P nuclear magnetic resonance (NMR) study, combined with thermodynamic measurements and first-principles band-structure calculations, has been conducted to explore the ground state of the 𝑆=5/2 double trillium lattice antiferromagnet KSrFe 2 ⁢(PO 4 ) 3 . Our experimental results indicate that the magnetic ground state is neither a conventional three-dimensional (3D) long-range order (LRO) nor a pure gapless spin-liquid state, as conjectured previously [Boya et al., APL Mater. 10, 101103 (2022)]. Specifically, the observation of a nearly field-independent NMR linewidth below 𝑇* = (3.5 ± 0.4)⁢ K, and a significant enhancement of spin-spin relaxation rate 1/𝑇 2 below 2⁢𝑇* (where 𝑇* is the characteristic temperature identified from the magnetic susceptibility), indicate a complex magnetic ground state where spin freezing coexists with persistent dynamics. Furthermore, we argue that the lack of magnetic LRO and the persistence of strong magnetic fluctuations in KSrFe 2 ⁢(PO 4 ) 3 are unlikely to originate from intersite K/Sr disorder, rather they arise due to intrinsic magnetic frustration. In conclusion, our findings position KSrFe 2 ⁢(PO 4 ) 3 into a broader family of geometrically frustrated magnets characterized by coexisting spin freezing and pronounced antiferromagnetic fluctuations, marking it as a promising platform for investigating exotic phenomena in 3D frustrated magnets.

Exotic phases of matter↗
DOE OSTI2020

Metabolic multistability and hysteresis in a model aerobe-anaerobe microbiome community

Major changes in the microbiome are associated with health and disease. Some microbiome states persist despite seemingly unfavorable conditions, such as the proliferation of aerobe-anaerobe communities in oxygen-exposed environments in wound infections or small intestinal bacterial overgrowth. Mechanisms underlying transitions into and persistence of these states remain unclear. Using two microbial taxa relevant to the human microbiome, we combine genome-scale mathematical modeling, bioreactor experiments, transcriptomics, and dynamical systems theory to show that multistability and hysteresis (MSH) is a mechanism describing the shift from an aerobe-dominated state to a resilient, paradoxically persistent aerobe-anaerobe state. We examine the impact of changing oxygen and nutrient regimes and identify changes in metabolism and gene expression that lead to MSH and associated multi-stable states. In such systems, conceptual causation-correlation connections break and MSH must be used for analysis. Using MSH to analyze microbiome dynamics will improve our conceptual understanding of stability of microbiome states and transitions between states.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Seroprevalence and risk factors for brucellosis amongst livestock and humans in a multi-herd ranch system in Kagera, Tanzania

Background Brucellosis remains a significant health and economic challenge for livestock and humans globally. Despite its public health implications, the factors driving the endemic persistence ofBrucellaat the human-livestock interface in Tanzania remain poorly elucidated. This study aimed to identify the seroprevalence ofBrucellainfection in livestock and humans within a ranching system and determine associated risk factors for disease endemicity. Methods A cross-sectional sero-epidemiological study was conducted in 2023 in Tanzania’s Karagwe District, involving 725 livestock (cattle, goats, sheep) from 10 herds and 112 humans from associated camps. Seroprevalence was assessed using competitive ELISA while epidemiological data were collected via questionnaires. Generalized Linear Models and Contrast Analysis were used to identify risk factors for infection. Results Overall seroprevalence was 34% in livestock and 41% in humans. Goats exhibited the highest prevalence (69.2%), while cattle had the lowest (22.6%). Mixed-species herds (Odds Ratio, OR = 2.96, CI [1.90–4.60]) and small ruminants-only herds (OR = 6.54, CI [3.65–11.72]) showed a significantly higher risk of seropositivity compared to cattle-only herds. Older cattle (OR = 5.23, CI [2.70–10.10]) and lactating females (OR = 2.87, CI [1.78–4.63]) represented significant risks for brucellosis in livestock. In humans, close contact with animals (OR = 7.20, CI [1.97–36.31]) and handling animals during parturition or aborted fetuses (OR = 2.37, CI [1.01–5.58]) were significant risk factors. Notably, no spatial association was found in seroprevalence between herds and nearby human communities. Conclusion The lack of spatial correlation between livestock and human seroprevalence suggests complex transmission dynamics, potentially involving endemic circulation in livestock and human infections from multiple sources of exposure to livestock. This study highlights the need for comprehensive zoonotic risk education and targeted intervention strategies. Further research is crucial to elucidate transmission pathways and improveBrucellainfection control. This includes developing robust methods for identifying infective species and implementing effective strategies to mitigateBrucellainfection in endemic regions.

Public, Environmental & Occupational Health↗
DOE OSTI2021

Evaluating State Space Discovery by Persistent Cohomology in the Spatial Representation System

Persistent cohomology is a powerful technique for discovering topological structure in data. Strategies for its use in neuroscience are still undergoing development. We comprehensively and rigorously assess its performance in simulated neural recordings of the brain's spatial representation system. Grid, head direction, and conjunctive cell populations each span low-dimensional topological structures embedded in high-dimensional neural activity space. We evaluate the ability for persistent cohomology to discover these structures for different dataset dimensions, variations in spatial tuning, and forms of noise. We quantify its ability to decode simulated animal trajectories contained within these topological structures. We also identify regimes under which mixtures of populations form product topologies that can be detected. Our results reveal how dataset parameters affect the success of topological discovery and suggest principles for applying persistent cohomology, as well as persistent homology, to experimental neural recordings.

59 BASIC BIOLOGICAL SCIENCES↗